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Research Machine Learning Federated Learning Jobs

Omni Inclusive

Machine Learning

Dallas, TX

Machine Learning - Decision Trees, Random Forests, Rule Mining, Clustering, PCA, Support Vector Machine, Ensemble techniques * Deep Learning - Neural networks, multilayer perceptron, word embeddings ...

HEB

Data Scientist - eCommerce

San Antonio, TX · On-site

$158K/yr

... machine learning process, and orchestrating reusable storytelling methodology to apply toward AI ... research to accelerate business innovation What is your background? - A related degree or ...

HEB

Data Scientist - eCommerce

San Antonio, TX

... machine learning process, and orchestrating reusable storytelling methodology to apply toward AI ... research to accelerate business innovation What is your background? - A related degree or ...

True Anomaly

Machine Learning Engineer

Long Beach, CA · On-site

They are seeking a Machine Learning Engineer to design and develop machine learning and AI ... Preferred : • Internship, research, or project experience applying ML to real-world or research ...

OpenAI

Research Engineer, Privacy

San Francisco, CA · On-site

$380K - $445K/yr

... machine-learning algorithms (e.g., differential privacy, secure aggregation, federated learning ... Have hands-on research or production experience with PETs. * Are fluent in modern deep-learning ...

SAIC

Machine Learning Developer

Arlington, VA · Hybrid

Conduct research to identify new approaches and methods for machine learning and AI. * Stay updated with the latest trends and advancements in machine learning and AI. * Document processes, codes ...

Avride

Machine Learning Engineer

Austin, TX · On-site

Additionally, you will analyze the latest research, assess the applicability of emerging deep ... Develop and Optimize Machine Learning Models: Design, implement, and refine deep learning models to ...

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Research Machine Learning Federated Learning information

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$25.5K

$42.6K

$88K

How much do research machine learning federated learning jobs pay per year?

As of Jun 11, 2026, the average yearly pay for research machine learning federated learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Researcher in Machine Learning Federated Learning, and why are they important?

To thrive as a Researcher in Machine Learning Federated Learning, you need a strong background in computer science, mathematics, and machine learning, typically supported by a relevant advanced degree (e.g., PhD or MSc). Familiarity with Python, TensorFlow, PyTorch, and distributed computing frameworks, as well as knowledge of privacy-preserving techniques and relevant research publications, is essential. Excellent analytical thinking, problem-solving abilities, and clear scientific communication are key soft skills for success in collaborative research environments. These competencies are vital to drive innovation, rigorously evaluate federated learning approaches, and advance privacy-preserving AI technologies.

What are some common challenges faced when implementing federated learning in a research environment?

One of the primary challenges in research-focused federated learning roles is ensuring data privacy and security while maintaining model performance across distributed devices. Researchers must also address issues such as handling heterogeneous data sources, communication bottlenecks between nodes, and the complexity of debugging decentralized systems. Collaborating with cross-functional teams—such as data engineers, privacy experts, and domain specialists—is vital to overcome these hurdles and drive successful outcomes. Staying updated with the latest advancements and actively contributing to open-source initiatives can also help researchers address these evolving challenges.

What is a Researcher in Machine Learning Federated Learning?

A Researcher in Machine Learning Federated Learning is a professional who investigates and develops methods to train machine learning models across multiple decentralized devices or servers, while keeping data localized and private. Their work focuses on improving algorithms, ensuring data privacy, and addressing challenges related to distributed learning, communication efficiency, and model accuracy. They often collaborate with other researchers, publish findings, and contribute to advancing technologies that make it possible to use sensitive data for AI without compromising privacy.

What is the difference between Research Machine Learning Federated Learning vs Data Scientist?

AspectResearch Machine Learning Federated LearningData Scientist
CredentialsAdvanced degrees in CS, ML, or related fields; research experienceBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentResearch labs, academic institutions, tech companies focusing on privacy-preserving MLBusiness environments, analytics teams, data-driven departments
Industry UsageDeveloping federated algorithms, privacy-preserving ML modelsData analysis, modeling, reporting, and insights generation

Research Machine Learning Federated Learning specialists focus on developing privacy-preserving algorithms across distributed data sources, often in research or R&D settings. Data Scientists analyze and interpret data to inform business decisions. While both roles require strong ML knowledge, federated learning roles emphasize distributed systems and privacy, whereas Data Scientists focus on data analysis and visualization.

More about Research Machine Learning Federated Learning jobs
What cities are hiring for Research Machine Learning Federated Learning jobs? Cities with the most Research Machine Learning Federated Learning job openings:
What states have the most Research Machine Learning Federated Learning jobs? States with the most job openings for Research Machine Learning Federated Learning jobs include:
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Research Machine Learning Federated Learning jobs near you
Infographic showing various Research Machine Learning Federated Learning job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Machine Learning

Omni Inclusive

Dallas, TX

Other

Posted 25 days ago

Job description

Job Title

Skill: At least 3 years of experience on the following:

  • Machine Learning – Decision Trees, Random Forests, Rule Mining, Clustering, PCA, Support Vector Machine, Ensemble techniques
  • Deep Learning - Neural networks, multilayer perceptron, word embeddings, categorical embedding, RNN and LSTM, word2vec, encoder/decoder models, attention and transformer models, transfer learning (ULMFiT), foundation models from Azure Open AI
  • Database - Snowflake, Oracle, Graph database
  • Programming & Scripting - Python, R, Unix-Shell scripting, PySpark

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